Great news, thanks for sharing. Important artickes like this, by the way, are better off copied and pasted on to the thread, GodConsciousness. The same with scientific papers that forum participants wish to share with us. That way the information will forever be available to our BM community, regardless of what happends to the original URL. So, I took the liberty of pasting the content of your link to the thread. I hope you don't mind!

$40 million awarded to trace human brain's connectionsSouped-up scanners to reveal intricate circuitry in high resolution

The National Institutes of Health today awarded grants totaling $40 million to map the human brain's connections in high resolution. Better understanding of such connectivity promises improved diagnosis and treatment of brain disorders.

The grants are the first awarded under the Human Connectome Project. They will support two collaborating research consortia. The first will be led by researchers at Washington University, St. Louis, and the University of Minnesota, Twin Cities. The other will be led by investigators at Massachusetts General Hospital (MGH)/Harvard University, Boston, and the University of California Los Angeles (UCLA).

"We're planning a concerted attack on one of the great scientific challenges of the 21st. Century," explained Washington University's Dr. David Van Essen, Ph.D., who co-leads one of the groups with Minnesota's Kamil Ugurbil, Ph.D. "The Human Connectome Project will have transformative impact, paving the way toward a detailed understanding of how our brain circuitry changes as we age and how it differs in psychiatric and neurologic illness."

The Connectome projects are being funded by 16 components of NIH under its Blueprint for Neuroscience Research.

"On a scale never before attempted, this highly coordinated effort will use state-of-the-art imaging instruments, analysis tools and informatics technologies – and all of the resulting data will be freely shared with the research community," said Michael Huerta, Ph.D., of the National Institute of Mental Health, who directs the NIH Connectome initiative. "Individual variability in brain connections underlies the diversity of our thinking, perception and motor skills, so understanding these networks promises advances in brain health."

The Washington U./Minnesota team will map the connectomes in each of 1,200 healthy adults – twin pairs and their siblings from 300 families. The maps will show the anatomical and functional connections between parts of the brain for each individual, and will be related to behavioral test data. Comparing the connectomes and genetic data of genetically identical twins with fraternal twins will reveal the relative contributions of genes and environment in shaping brain circuitry and pinpoint relevant genetic variation. The maps will also shed light on how brain networks are organized.

In tooling up for the screening, the researchers will optimize magnetic resonance imaging (MRI) scanners to capture the brain's anatomical wiring – and its activity, both when participants are at rest and when challenged by tasks. All participants will undergo such structural and functional scans at Washington University. For these, researchers will use a customized MRI scanner with a magnetic field of 3 Tesla. This Connectome Scanner will incorporate new imaging approaches developed by consortium scientists at Minnesota and Advanced MRI Technologies and will provide ten-fold faster imaging times and better spatial resolution.

Additionally, a subset of twin pairs will also be scanned using more powerful 7 and 10.5 Tesla MRI units at the University of Minnesota, which has pioneered the use of such advanced, ultra high magnetic field imaging. For another subset of twins, the scans will be complemented by movies of millisecond brain electrical activity obtained at St. Louis University, using magnetoencephalography (MEG) and electroencephalography (EEG).

After processing with sophisticated analysis tools using a supercomputer, the data will become web accessible via a customized Connectome Database Neuroinformatics Platform. All-told, the $30 million five-year project will involve 33 collaborators from nine research centers, including Oxford University, U.K.; Indiana University, Bloomington; University of California, Berkeley; Warwick University, U.K.; University d'Annunzio, Italy; and the Ernst Strungmann Institute, Germany.

Also collaborating with this larger project, the MGH/Harvard-UCLA Connectome consortium will focus on optimizing MRI technology for imaging the brain's structural connections using diffusion MRI with unprecedented resolution. This way of using a MRI scanner, employed in both projects, maps the brain's fibrous long distance connections by tracking the motion of water. Different types of tissues are detectable by telltale water diffusion patterns characteristic of different types of cells. So the long extensions of neurons, called white matter, can been seen in sharp relief.

"The MRI scanner system we are assembling will be 4 to 8 times as powerful as conventional systems, enabling imaging of human neuroanatomy with much greater sensitivity than is currently possible," explained Bruce Rosen, M.D., Ph.D., who is co-directing the project with MGH/Harvard colleague Van Wedeen, M.D., and Arthur Toga, Ph.D., of UCLA.

The planned Connectome Scanner, to be built by Siemens Medical Systems for this project, is the first of a new class of MRI instruments. It will boost resolving power while also shortening the scan times required to image each subject, Rosen said.

The MGH/Harvard team has pioneered the use of a diffusion MRI technique called Diffusion Spectrum Imaging (DSI) to create stunning maps of neural fibers crisscrossing the brain. DSI offers a higher resolution, more multidimensional view than an older technique called Diffusion Tensor Imaging. This makes it possible, for example, to see the different orientations of multiple neural fibers that cross at a single location.

"Today we know less about the connectivity of the human brain than about a dozen other species," said Wedeen. "Learning more about variation in our own brain's connections will lay the groundwork for using brain imaging measures of connectivity as an aid in diagnosis."

"Creating these maps requires sophisticated statistical and visual informatics approaches," added UCLA's Toga. "Understanding the similarities and differences in these maps among sub-populations will improve our understanding of human brain in health and disease."

Supported by an $8.5 million grant over three years, the project will scan healthy adults, including some participants from the other consortia's project. Data and research know-how will also be shared across the two projects.

###The National Institutes of Health (NIH) — The Nation's Medical Research Agency — includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. It is the primary federal agency for conducting and supporting basic, clinical and translational medical research, and it investigates the causes, treatments, and cures for both common and rare diseases. Visit the NIH website for more information about NIH and its programs.

The NIH Blueprint for Neuroscience Research is a cooperative effort among the NIH Office of the Director and the 15 NIH Institutes and Centers that support research on the nervous system. By pooling resources and expertise, the Blueprint supports transformative neuroscience research, and the development of new tools, training opportunities, and other resources to assist neuroscientists.

Curious if the new MRI scanners they will be using will be able to generate the necessary resolution for a proper connectome map. Can the new resolution MRI scanners compare to serial block face scanning electron microscopy? Curious to get LD's thoughts on this.

Curious if the new MRI scanners they will be using will be able to generate the necessary resolution for a proper connectome map. Can the new resolution MRI scanners compare to serial block face scanning electron microscopy? Curious to get LD's thoughts on this.

MRI resolution is on the order of a 1 mm, whereas the finest axons in the brain are 50 nm in diameter, which is 20,000 times smaller. What this means is that, for each cubic mm of the brain, there could be as many as (20,000)^2, or 40 million axons passing through. Because MRI relies on water diffusion, which is an indirect measure of connectivity, you can never be certain that the connections you map using DTI or DSI are actually correct. In short, DTI/DSI will very likely never approach the resolution needed for mapping out real connections in the brain, and it will be limited to mapping out coarse fiber bundles, which means it will never reveal information about the intricate wiring in the brain. However, the big advantage to DTI/DSI is that it can be done in vivo, and I think it might find an important role in disease diagnosis. But for mapping brain connectivity, it's wishful thinking to expect that MRI will ever reveal anything significant in this regard, beyond mapping coarse fiber bundles. You can also use tracer injections or transgenic approaches with light microscopy, but at the cost of sparse sampling, and inability to resolve synapses, and in the end, these approaches are incapable of yielding a circuit diagram for an individual brain. The only approach currently, for mapping the intricate connectivity of the brain, is electron microscopy, because that is the only technique with the required resolution for densely mapping individual axons.

The only approach currently, for mapping the intricate connectivity of the brain, is electron microscopy, because that is the only technique with the required resolution for densely mapping individual axons.

How far advanced is that technology? If water depending mapping (or molecule size sensitivity, if you want to look at it that way) is only news now, electron microscopy sound like a pipe dream for right now.And, more importantly, will that technique be the final frontier in terms of brain mapping, or will it just bring up more questions than answers?

electron microscopy (both TEM and SEM) is not dead in any sense. It is currently not being hyped as much as DTI and DSI, but there are reasons for that, including the fact that very few labs are in a position to invest heavily in EM technology to bring it to a point for whole-brain imaging. See http://www.ncbi.nlm.nih.gov/pubmed/16962767 for an example of where this technology is headed, and this was published in 2006. Currently, EM technology, and its application to whole-brain mapping, is at a position where it's just a question of time (i.e., not 'if' but 'when') it blows DTI and DSI out of the water (pun intended).

If you read the Methods section of any DSI paper, you'll be struck by how far from actual neural connectivity its results are. It's not just a question of millimeter size voxels (which are 20,000 times the size of individual axons) and the fact that measuring water diffusion is an indirect measure of connectivity, but also the fact that it lacks a method of verification. Also consider how people employing DSI generate "fibers"; they start by arbitrarily assigning thousands of seed points to random locations within each white matter voxel and then tracing them out by relying on the local maxima of the measured water diffusion. This has nothing to do with how axons and fiber tracts are actually organized in the brain, so you have to take any DSI map with a huge grain of salt.

I wish I could say that DSI is just a fad, but because it can be done in vivo, whereas electron microscopy cannot, I suspect DSI will be around for a while for disease diagnosis. However, its relevance for mapping actual brain connectivity is highly doubtful. It is capable of generating pretty pictures of "fibers" in the brain, but these fibers have no neuroanatomical relevance, and the methodology as such is akin to intellectual masturbation.

Wishful thinking alone does not transform implausible data (i.e., the DSI "fibers") into the plausible. For an actual map of neural connections throughout the whole brain, you really do need electron microscopy, and this technology is at a point where it is assured to be delivering a lot of results, soon. A little patience may be in order, but these electron microscopic whole-brain maps are forthcoming.

Sounds like we will eventually need something akin to electron microscopy for more refined medical diagnoses. The MRIs may be one of the best tools for now, but if brain circuitry maps are going to be properly utilized in medicine, we will need nearly identical levels of resolution.

now that's very funny. I think normally, most people would not have misinterpreted your statement, but in my case, I was thinking that a few years ago, many people were pessimistic about EM for circuit mapping, and so I thought you were expressing those sentiments.

now that's very funny. I think normally, most people would not have misinterpreted your statement, but in my case, I was thinking that a few years ago, many people were pessimistic about EM for circuit mapping, and so I thought you were expressing those sentiments.

These may be questions best handled by LD but if anyone has some thoughts I would appreciate further clarification. From what I am gathering, the DSI technique is not likely to give us an accurate circuit map (to say the least). I am wondering how confocal laser scanning microscopy compares to electron microscopy. It appears that multiphoton laser scanning microscopy may be able to obtain finer resolution than confocal microscopy, but it seems that they cannot reach the nanometer level of resolution. Is electron microscopy the only way to reach nanometer resolution? Is there any benefit in attempting to build a connectome map with laser microscopy AND electron microscopy? Or is the laser microscopy only going to be able to verify the circuits revealed by electron microscopy, but still miss a fair number of circuits because laser microscopy cannot reach the nanometer level? Is light microscopy the same as laser scanning microscopy?

because of the Nyquist limit, light microscopy cannot get below 100 micron resolution. Super-resolution techniques offer the possibility of circumventing this, and the idea has been floated around to try this with BrainBow transgenic mice, where each neuron expresses a unique XMP combination. However, there are some serious technical issues with this approach that, in my opinion, make it unlikely that BrainBow transgenic mice and light microscopy can be used for circuit mapping. Of course, I could be proved wrong, but I think it's unlikely, which means that electron microscopy is that only way to currently map brain circuits, and will likely remain the only way, unless a revolutionary new method is devised.

Magnetic resonance force microscopy (MRFM) relies on detecting very small magnetic forces. In addition to its high resolution, MRFM has the further advantage that it is chemically specific, can "see" below surfaces and, unlike electron microscopy, does not destroy delicate biological materials.

An IBM-led team has dramatically boosted the sensitivity of MRFM and combined it with an advanced 3D image reconstruction technique. This allowed them to demonstrate, for the first time, MRI on biological objects at the nanometre scale.

The technique was applied to a sample of tobacco mosaic virus and achieved resolution down to four nanometres (one nanometre is one billionth of a metre; a tobacco mosaic virus is 18 nanometres across)."MRI is well known as a powerful tool for medical imaging, but its capability for microscopy has always been very limited," said Dan Rugar, manager of nanoscale studies at IBM Research.

"Our hope is that nano MRI will eventually allow us to directly image the internal structure of individual protein molecules and molecular complexes, which is key to understanding biological function."

LD- I am also wondering if you would be willing to comment on the Blue Brain Project. Are they attempting to build a connectome map using purely computer models? Are they using any of the scanning technologies we have been discussing here?

HH, as far as i can tell, MRFM is akin to atomic force microscopy in requiring a cantilever to probe a sample surface, and seems restricted to an imaging depth of a few tens of nm, which means that you would have to destroy a larger 3D volumetric sample to image it, just like in EM, unless you were only interested in features close to the surface. Also, the field of view (FOV) for MRFM is on the order of a few hundred nm, which would be insufficient for imaging axons that travel for several mm. It's not clear whether you could scale up the FOV, and this, at first glance, would appear the main issue, since a mouse brain, for example, is 1 cm in linear dimension. There would be other issues to consider, too, such as signal-to-noise and acquisition rates. It does look like an interesting method. I would like to see more examples of it in use, since all I have seen so far in papers is imaging of viruses.

GD, yes, 2-photon appears to be in the past and SBFSEM at the forefront. It's not unreasonable to expect SBFSEM to acquire the same ubiquity as 2-photon in the coming years, particularly once its utility for mapping neural circuits is more strongly demonstrated.

The Blue Brain Project (BBP) is a large-scale computer simulation of a mouse cortical column, which will be scaled up to encompass the entire mouse brain within a couple of years, and ultimately, the human brain in 10 yrs. On the computer side (modeling and simulation), the BBP is strong, and is probably one of the top, if not the top, project for large scale neuronal simulation. Its Achilles' heel is the profound lack of empirical data on which the models are based, and on which the simulations are run. The lack of empirical neuroanatomical data is glaring; and the way that Markram justifies the statistical connectivity used in the BBP fails. But also, the physiological data is weak since empirically, we do not know precisely how ion channels are distributed across neurons for all different cell classes. And on top of that, we still don't have a firm grasp, empirically, on synaptic plasticity as a function of cell type. The BBP simulations are run with as much as 99% of empirical data not known, and so they just make up values to fill in the gaps. One might argue that it's GIGO. But on the bright side, once the connectivity and other parameters are empirically determined by other research groups, then there's little doubt that the BBP will be useful for realistic neural circuit simulation.

THANKS LD! Your insights have brought much more clarity (no pun intended) to some of the key issues here. Looks like your work with Denk at Max Planck and Lichtman's lab at Harvard are the two top places where a true connectome map is likely to emerge. I hope more labs can get on the same page and help collaborate your efforts.

Unfortunately, despite the large amount of NIH funds and team of researchers dedicated to the human connectome project referred to in the OP, they are not likely to generate a true map.

desc: ZhiBike is the product of our sales agents, there are a variety of the latest style in 2009, including Forks, Stems, Bashrings, Cranks(158m), Cranks(170m), Handlebars, Hub(Front,Disc), Frames(20), Frames(26) and more. Welcome to our web site